Top > JRM > Grasp Planning for a Multifingered Hand with a Humanoid Robot

single-rb.php

JRM Vol.22 No.2 pp. 230-238
doi: 10.20965/jrm.2010.p0230
(2010)

Paper:

Views over last 60 days: 534

Grasp Planning for a Multifingered Hand with a Humanoid Robot

Tokuo Tsuji, Kensuke Harada, Kenji Kaneko, Fumio Kanehiro,
and Kenichi Maruyama

Intelligent Systems Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), AIST Central 2, 1-1-1 Umezono, Tsukuba, Ibaraki 305-8568, Japan

Received:
October 20, 2009
Accepted:
February 16, 2010
Published:
April 20, 2010
Creative Commons License
Keywords:
multifingered hand, humanoid robot, grasp planning, OpenRTM, force closure
Abstract
This paper presents grasp planning for a multifingered hand with a humanoid robot. Our planner selects different ways of grasping even for the same object according to object position/orientation. If the planner cannot find a feasible grasp with arm/hand kinematics, it switches to full body motion planning. These functions are necessary for realizing the robust grasp planning. Our planner defines convex models on both the object and each grasp type. In considering geometrical relationships among these convex models, we determine the parameters required to define the final grasping configuration. We demonstrate effectiveness of grasp planning through simulation and experimental results.
Cite this article as:
T. Tsuji, K. Harada, K. Kaneko, F. Kanehiro, and K. Maruyama, “Grasp Planning for a Multifingered Hand with a Humanoid Robot,” J. Robot. Mechatron., Vol.22 No.2, pp. 230-238, 2010.
Data files:
References
  1. [1] I. A. Kapandji, “Physiologie Architecture,” Maloine S. A. Editeur, 1985.
  2. [2] K. Akachi, K. Kaneko, N. Kanehira, S. Ota, G. Miyamori, M. Hirata, S. Kajita, and F. Kanehiro, “Development of Humanoid Robot HRP-3P,” IEEE-RAS/RSJ Int. Conf. on Humanoid Robots, 2005.
  3. [3] K. Kaneko, K. Harada, and F. Kanehiro, “Development of Multifingered Hand for Life-size Humanoid Robots,” IEEE Int. Conf. on Robotics and Automation, pp. 913-920, 2007.
  4. [4] K. B. Shimoga, “Robot Grasp Synthesis: A Survey,” Int. J. of Robotics Research, Vol.5, No.3, 1996.
  5. [5] K. Harada, K. Kaneko, and F. Kanehiro, “Fast Grasp Planning for Hand/Arm Systems based on Convex Modes,” Proc. IEEE Int. Conf. on Robotics and Automation, 2008.
  6. [6] OpenRTM: http://www.is.aist.go.jp/rt/OpenRTM-aist/
  7. [7] N. Niparnan and A. Sudsang, “Fast Computation of 4-Fingered Force-Closure Grasps from Surface Points,” IEEE/RSJ Int. Conf. Intelligent Robots and Systems, 2004.
  8. [8] J. A. Coelho Jr. and R. A. Grupen, “Online Grasp Synthesis,” IEEE Int. Conf. on Robotics and Automation, 1996.
  9. [9] J. Ponce, S. Sullivan, J. D. Boissonnat, and J. P. Merlet, “On Characterizing and Computing Three- and Four-fingered Force Closure Grasps of Polygonal Objects,” IEEE Int. Conf. on Robotics and Automation, 1993.
  10. [10] M. R. Cutkosky, “On Grasp Choice, Grasp Models, and the Design of Hands for Manufacturing Tasks,” IEEE Trans. on Robotics and Automation, Vol.5, No.3, 1989.
  11. [11] N. S. Pollard, “Closure and Quality Equivalence for Efficient Synthesis of Grasps from Examples,” Int. J. of Robotics Research, Vol.23, No.6, pp. 595-613, 2004.
  12. [12] A. Morales, P. J. Sanz, A. P. del Pobil, and A. H. Fagg, “Vision-Based Three-Finger Grasp Synthesis Constrained by Hand Geometry,” Robotics and Autonomous Systems, No.54, 2006.
  13. [13] A. Morales, T. Asfour, and P. Azad, “Integrated Grasp Planning and Visual Object Localization for a Humanoid Robot with Five-Fingered Hands,” IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, 2006.
  14. [14] M. Prats, P. J. Sanz, and P. del Pobil, “Task-Oriented Grasping using Hand Preshapes and Task Frames,” IEEE Int. Conf. on Robotics and Automation, 2007.
  15. [15] C. Borst, M. Fischer, and G. Hirzinger, “A fast and Robust Grasp Planner for Arbitrary 3D Objects,” IEEE Int. Conf. on Robotics and Automation, 1999.
  16. [16] A. T. Miller, S. Knoop, H. I. Christensen, and P. K. Allen, “Automatic Grasp Planning using Shape Primitives,” IEEE Int. Conf. on Robotics and Automation, 2003.
  17. [17] A. T. Miller and P. K. Allen, “Grasp It!: A Versatile Simulator for Grasp Analysis,” ASME Int. Mechanical Engineering Congress & Exposition, 2000.
  18. [18] R. Pelossof, A. Miller, P. Allen, and T. Jebra, “An SVM Learning Approach to Robotic Grasping,” IEEE Int. Conf. on Robotics and Automation, 2004.
  19. [19] S. Ekvall and D. Kragic, “Learning and Evaluation of the Approach Vector for Automatic Grasp Generation and Planning,” IEEE Int. Conf. on Robotics and Automation, 2007.
  20. [20] C. Borst, M. Fischer, and G. Hirzinger, “Grasping the Dice by Dicing the Grasp,” IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, 2003.
  21. [21] M. Yashima, Y. Shiina, and H. Yamaguchi, “Randomized Manipulation Planning for A Multi-Fingered Hand by Switching Contact Modes,” IEEE Int. Conf. on Robotics and Automation, 2003.
  22. [22] C. Goldfeder, P. K. Allen, C. Lackner, and R. Pelossof, “Grasp Planning via Decomposition Trees,” IEEE Int. Conf. on Robotics and Automation, 2007.
  23. [23] K. Huebner, S. Ruthotto, and D. Kragic, “Minimum Volume Bounding Box Decomposition for Shape Approximation in Robot Grasping,” IEEE Int. Conf. on Robotics and Automation, 2008.
  24. [24] J. Bohg, C. Barck-Holst, K. Huebner, M. Ralph, B. Rasolzadeh, D. Song, and D. Kragic, “Towards Grasp-Oriented Visual Perception for Humanoid Robots,” Int. J. of Humanoid Robotics, Vol.6, No.3, pp. 387-434, 2009.
  25. [25] T. Tsuji, K. Harada, and K. Kaneko, F. Kanehiro, and Y. Kawai, “Selecting a Suitable Grasp Motion for Humanoid Robots with a Multi-Fingered Hand,” Proc. IEEE-RAS Int. Conf. on Humanoid Robots, pp. 54-60, 2008.
  26. [26] T. Tsuji, K. Harada, and K. Kaneko, “Easy and Fast Evaluation of Grasp Stability by Using Ellipsoidal Approximation of Friction Cone,” Proc. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, 2009.
  27. [27] MPK: http://robotics.stanford.edu/˜mitul/mpk/
  28. [28] K. Maruyama, Y. Kawai, and F. Tomita, “Model-based 3D Object Localization Using Occluding Contours,” Proc. 9th ACCV, MP3-20, 2009.

Creative Commons License  This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

Copyright© 2010 by Fuji Technology Press Ltd. and Japan Society of Mechanical Engineers. All right reserved.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Dec. 13, 2024